The Problem of Terroir in the Anthropocene
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Climate is integral to the concept of terroir. With anthropogenic climate change, the terroir of the worldâs winegrowing regions is changing, and will continue to change for decades or centuries. The clearest signal of this shift comes from the earlier harvests of winegrapes over the last several decades with harvests 2â3 weeks earlier in France and other regions. These earlier harvests have reshaped the climatic profile under which berries ripen, leading to wines with higher alcohol and shifted phenolic and aromatic attributes. But these shifts also hint at a major way to adapt viticulture to climate changeâthrough matching variety phenology to the current and future climates of established winegrowing regions. Here I show how variety phenologyâthe timing of major growth and reproductive events including budburst, flowering, veraison and harvestâis a critical component of terroir and one that is becoming increasingly mismatched due to climate change. I outline how growers and researchers alike can leverage current and new data to help develop a framework to shift varieties with climate change, and discuss how this could help build a more dynamic definition of terroirâone that embraces the challenges, and potential opportunities, of the Anthropocene.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it